Set up

suppressPackageStartupMessages({
  library(tidyverse)
})

Directories and File Inputs/Outputs

# Detect the ".git" folder -- this will be in the project root directory
# Use this as the root directory to ensure proper sourcing of functions 
# no matter where this is called from
root_dir <- rprojroot::find_root(rprojroot::has_dir(".git"))
analysis_dir <- file.path(root_dir, "analyses", "tmb-vaf-longitudinal")
results_dir <- file.path(analysis_dir, "results")
input_dir <- file.path(analysis_dir, "input")
files_dir <- file.path(root_dir, "analyses", "sample-distribution-analysis", "results")

# Input files for the paired longitudinal (PL) cohort
pbta_file <- file.path(files_dir, "pbta.tsv") # file from add-sample-distribution module
genomic_paired_file <- file.path(files_dir, "genomic_assays_matched_time_points.tsv")
tmb_vaf_file <- file.path(results_dir, "tmb_vaf_genomic.tsv")
palette_file <- file.path(root_dir, "figures", "palettes", "oncoprint_color_palette.tsv")


# Input files for the PBTA cohort
maf_file <- file.path(results_dir, "maf.tsv")
tmb_file <- file.path(input_dir, "snv-mutation-tmb-coding.tsv")


# File path to PL plot directory
PL_plots_dir <-
  file.path(analysis_dir, "plots", "Alteration_type_barplots_PL")
if (!dir.exists(PL_plots_dir)) {
  dir.create(PL_plots_dir)
}

# File path to kids_PL_plots directory
kids_PL_plots_dir <-
  file.path(PL_plots_dir, "kids_PL_plots")
if (!dir.exists(kids_PL_plots_dir)) {
  dir.create(kids_PL_plots_dir)
}

# File path to kids_molecular_subtype_PL_plots_dir directory
kids_molecular_subtype_PL_plots_dir <-
  file.path(PL_plots_dir, "kids_molecular_subtype_PL_plots")
if (!dir.exists(kids_molecular_subtype_PL_plots_dir)) {
  dir.create(kids_molecular_subtype_PL_plots_dir)
}


# File path to molecular_subtype_PL_plots directory
molecular_subtype_PL_plots_dir <-
  file.path(PL_plots_dir, "molecular_subtype_PL_plots")
if (!dir.exists(molecular_subtype_PL_plots_dir)) {
  dir.create(molecular_subtype_PL_plots_dir)
}

# File path to PBTA plot directory
PBTA_plots_dir <-
  file.path(analysis_dir, "plots", "Alteration_type_barplots_PBTA")
if (!dir.exists(PBTA_plots_dir)) {
  dir.create(PBTA_plots_dir)
}


# File path to molecular_subtype_PBTA_plots directory
molecular_subtype_PBTA_plots_dir <-
  file.path(PBTA_plots_dir, "molecular_subtype_PBTA_plots")
if (!dir.exists(molecular_subtype_PBTA_plots_dir)) {
  dir.create(molecular_subtype_PBTA_plots_dir)
}

source(paste0(root_dir, "/figures/scripts/theme.R"))
source(paste0(analysis_dir, "/util/function-create-barplot.R"))

Read in data and process

# Vector to order timepoints
timepoints_order <- c("Diagnosis", "Progressive", "Recurrence", "Deceased", "Second Malignancy", "Unavailable", "Metastatic", "Residual")
timepoints_order_abbrev <- c("Dx", "Pro", "Rec", "Dec", "SM", "Unavail", "Metastatic", "Residual")

# Vector to order Variant_Classification
variants_order <- c("Frame_Shift_Del", "Frame_Shift_Ins", "In_Frame_Del", 
                    "In_Frame_Ins", "Missense_Mutation", "Nonsense_Mutation", 
                    "Nonstop_Mutation", "Splice_Site", "Translation_Start_Site")

PL cohort

pbta_df <- readr::read_tsv(pbta_file, guess_max = 100000, show_col_types = FALSE) %>% 
  select(Kids_First_Participant_ID, Kids_First_Biospecimen_ID, cg_multiple, cg_id, cgGFAC, tumor_descriptor, molecular_subtype) %>%  #plot_group
  mutate(tumor_descriptor_abbrev = case_when(grepl("Diagnosis", tumor_descriptor) ~ "Dx",
                               grepl("Progressive", tumor_descriptor) ~ "Pro",
                               grepl("Recurrence", tumor_descriptor) ~ "Rec",
                               grepl("Deceased", tumor_descriptor) ~ "Dec",
                               grepl("Second Malignancy", tumor_descriptor) ~ "SM",
                               grepl("Unavailable", tumor_descriptor) ~ "Unavail",
                              TRUE ~ tumor_descriptor),
         molecular_subtype = str_replace(molecular_subtype, ",", ""),
         molecular_subtype_edited = str_replace(molecular_subtype, "^\\S* ", ""),
         
         # create unique identifier for timepoint and molecular subtype
         td_ms_plot_group = paste(tumor_descriptor_abbrev, molecular_subtype_edited, sep = ":")) 
  

# This includes non synonymous mutations as described in the `01-preporcess-data.Rmd`
tmb_vaf_df <- readr::read_tsv(tmb_vaf_file, guess_max = 100000, show_col_types = FALSE) %>% 
  filter(!tmb >= 10) %>% 
  select(Kids_First_Biospecimen_ID, Variant_Classification, gene_protein, mutation_count,   region_size, tmb, VAF) %>% 
  filter(!is.na(Variant_Classification))

# List with patients with paired longitudinal genomic specimens
genomic_paired_df <- readr::read_tsv(genomic_paired_file, guess_max = 100000, show_col_types = FALSE) %>%
  left_join(pbta_df, by = c("Kids_First_Participant_ID")) %>% 
  left_join(tmb_vaf_df, by = c("Kids_First_Biospecimen_ID")) %>%
  filter(!is.na(tmb))

# Number of patients with TMB information
no_samples_with_tmb <- print(length(unique(genomic_paired_df$Kids_First_Participant_ID)))
[1] 116
# Attention as some bs specimen might not have TMB.
# If that happens, we will end up with samples lacking timepoints.
# Let's identify these samples and remove them.
PL_df <- genomic_paired_df %>%
  select(Kids_First_Participant_ID, tumor_descriptor) %>% 
  unique() %>%
  arrange(Kids_First_Participant_ID, tumor_descriptor) %>%
  group_by(Kids_First_Participant_ID) %>%
  summarize(tumor_descriptor_sum = str_c(tumor_descriptor, collapse = ";")) %>%
  filter(!tumor_descriptor_sum %in% c("Diagnosis", "Progressive", "Recurrence", "Second Malignancy", "Unavailable", "Deceased", "Progressive;Progressive")) %>%
  left_join(genomic_paired_df, by = c("Kids_First_Participant_ID")) %>%
  filter(!cg_id == "NA",
         !tumor_descriptor == "Not Reported") %>% 
  mutate(match_id = paste(tumor_descriptor, Kids_First_Participant_ID, sep = "_"),
         cg_id = str_replace(cg_id, c("/|-"), " "))
  
# Let's summarize td_ms_plot_group and use this for visualization purposes
PL_td_ms_plot_group_n_df <- PL_df %>% 
  dplyr::count(cg_id, td_ms_plot_group) %>% 
  dplyr::mutate(td_ms_plot_group_n = glue::glue("{td_ms_plot_group} (N={n})")) %>% 
  dplyr::rename(td_ms_plot_group_number = n) 


# Let's summarize tumor_descriptor and use this for visualization purposes
PL_td_plot_group_n_df <- PL_df %>% 
  dplyr::count(cg_id, tumor_descriptor) %>% 
  dplyr::mutate(td_plot_group_n = glue::glue("{tumor_descriptor} (N={n})")) %>% 
  dplyr::rename(td_plot_group_number = n)

# Let's count number of samples 
PL_count_df <- PL_df %>%
  left_join(PL_td_ms_plot_group_n_df) %>%
  left_join(PL_td_plot_group_n_df) %>%
  filter(!is.na(Variant_Classification)) %>% 
  # remove if total #samples per timepoint is less than 2
  #filter(!td_ms_plot_group_number <= 2) %>% 
  group_by(tumor_descriptor, td_ms_plot_group, cg_id, molecular_subtype, Kids_First_Participant_ID, match_id, Variant_Classification, td_ms_plot_group_n, td_plot_group_n) %>% 
  dplyr::count(Kids_First_Participant_ID) %>% 
  mutate(tumor_descriptor = factor(tumor_descriptor),
         tumor_descriptor = fct_relevel(tumor_descriptor, timepoints_order),
         Variant_Classification = factor(Variant_Classification),
         Variant_Classification = fct_relevel(Variant_Classification, variants_order)) %>% 
  arrange(cg_id, tumor_descriptor, td_plot_group_n, Variant_Classification, desc(molecular_subtype)) 
Joining with `by = join_by(cg_id, td_ms_plot_group)`Joining with `by = join_by(cg_id, tumor_descriptor)`Warning: There were 945 warnings in `mutate()`.
The first warning was:
ℹ In argument: `tumor_descriptor = fct_relevel(tumor_descriptor, timepoints_order)`.
ℹ In group 1: `tumor_descriptor = "Deceased"`, `td_ms_plot_group = "Dec:ADAM"`, `cg_id = "Adamantinomatous Craniopharyngioma"`, `molecular_subtype =
  "CRANIO ADAM"`, `Kids_First_Participant_ID = "PT_WYXTEG3E"`, `match_id = "Deceased_PT_WYXTEG3E"`, `Variant_Classification = "Frame_Shift_Del"`,
  `td_ms_plot_group_n = "Dec:ADAM (N=21)"`, `td_plot_group_n = "Deceased (N=21)"`.
Caused by warning:
! 3 unknown levels in `f`: Unavailable, Metastatic, and Residual
ℹ Run ]8;;ide:run:dplyr::last_dplyr_warnings()dplyr::last_dplyr_warnings()]8;; to see the 944 remaining warnings.
# Number of patients with TMB information and paired timepoints
no_samples <- print(length(unique(PL_count_df$Kids_First_Participant_ID)))
[1] 107

PBTA cohort

tmb_df <- readr::read_tsv(tmb_file, guess_max = 100000, show_col_types = FALSE) %>% 
  dplyr::rename(Kids_First_Biospecimen_ID = Tumor_Sample_Barcode) # change name of the biospecimen to match the one from the histologies files

tmb_vaf_df <- readr::read_tsv(maf_file, guess_max = 100000, show_col_types = FALSE) %>%
  left_join(tmb_df, by = c("Kids_First_Biospecimen_ID")) %>% 
  filter(!tmb >= 10,
         !is.na(tmb)) 

PBTA_df <- pbta_df %>% 
  left_join(tmb_vaf_df, by = c("Kids_First_Biospecimen_ID")) %>% 
  filter(!cg_id == "NA",
         !tumor_descriptor == "Not Reported",
         !is.na(Variant_Classification)) %>% 
  mutate(match_id = paste(tumor_descriptor, Kids_First_Participant_ID, sep = "_"),
         cg_id = str_replace(cg_id, c("/|-"), " "))

# Number of patients with TMB information
no_samples <- print(length(unique(PBTA_df$Kids_First_Participant_ID)))
[1] 1850
# Let's summarize tumor_descriptor and use this for visualization purposes
PBTA_td_plot_group_n_df <- PBTA_df %>% 
  dplyr::count(cg_id, tumor_descriptor) %>% 
  dplyr::mutate(td_plot_group_n = glue::glue("{tumor_descriptor} (N={n})")) %>% 
  dplyr::rename(td_plot_group_number = n)

# Let's count number of samples 
PBTA_count_df <- PBTA_df %>% 
  left_join(PBTA_td_plot_group_n_df, by = join_by("cg_id", "tumor_descriptor")) %>% 
  filter(!is.na(Variant_Classification)) %>% 
  group_by(tumor_descriptor, cg_id, molecular_subtype, Kids_First_Participant_ID, match_id, Variant_Classification, td_plot_group_n) %>% 
  dplyr::count(Kids_First_Participant_ID) %>% 
  mutate(tumor_descriptor = factor(tumor_descriptor),
         tumor_descriptor = fct_relevel(tumor_descriptor, timepoints_order),
         Variant_Classification = factor(Variant_Classification),
         Variant_Classification = fct_relevel(Variant_Classification, variants_order)) %>% 
  arrange(cg_id, tumor_descriptor, td_plot_group_n, Variant_Classification, desc(molecular_subtype)) 
Warning: There were 6564 warnings in `mutate()`.
The first warning was:
ℹ In argument: `tumor_descriptor = fct_relevel(tumor_descriptor, timepoints_order)`.
ℹ In group 1: `tumor_descriptor = "Deceased"`, `cg_id = "Adamantinomatous Craniopharyngioma"`, `molecular_subtype = "CRANIO ADAM"`,
  `Kids_First_Participant_ID = "PT_WYXTEG3E"`, `match_id = "Deceased_PT_WYXTEG3E"`, `Variant_Classification = "Frame_Shift_Del"`, `td_plot_group_n =
  "Deceased (N=21)"`.
Caused by warning:
! 1 unknown level in `f`: Unavailable
ℹ Run ]8;;ide:run:dplyr::last_dplyr_warnings()dplyr::last_dplyr_warnings()]8;; to see the 6563 remaining warnings.

Define parameters for plots

# Read color palette
palette_df <- readr::read_tsv(palette_file, guess_max = 100000, show_col_types = FALSE) %>% 
  mutate(hex_codes = case_when(grepl("#000000", hex_codes) ~ "orange",
                               TRUE ~ hex_codes),
    color_names = factor(color_names),
         color_names = fct_relevel(color_names, variants_order)) %>% 
  arrange(color_names)

         
# Define and order palette
palette <- palette_df$hex_codes
names(palette) <- palette_df$color_names

Alterations per timepoint

PL cohort

# Define parameters for function
x_value <- PL_count_df$tumor_descriptor
title <- paste("Variant types in the paired longitudinal cohort", sep = " ")

# Run function
fname <- paste0(PL_plots_dir, "/", "Alteration_type_timepoints_barplots_PL.pdf")
print(fname)
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/Alteration_type_timepoints_barplots_PL.pdf"
p <- create_stacked_barplot_variant(df = PL_count_df, x = x_value, palette = palette, title = title)
pdf(file = fname, width = 6, height = 6)
print(p)
dev.off()
quartz_off_screen 
                2 

PBTA cohort

# Define parameters for function
x_value <- PBTA_count_df$tumor_descriptor
title <- paste("Variant types in the PBTA cohort", sep = " ")

# Run function
fname <- paste0(PBTA_plots_dir, "/", "Alteration_type_timepoints_barplots_PBTA.pdf")
print(fname)
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/Alteration_type_timepoints_barplots_PBTA.pdf"
p <- create_stacked_barplot_variant(df = PBTA_count_df, x = x_value, palette = palette, title = title)
pdf(file = fname, width = 6, height = 6)
print(p)
dev.off()
quartz_off_screen 
                2 

Alterations per timepoint in each cancer type

PL cohort

PL_panel_df <- PL_count_df %>% 
  mutate(cg_id = str_wrap(cg_id, 12)) # Edit to fit in the plot title for the panel

# Define parameters for function
x_value <- PL_panel_df$tumor_descriptor
title <- paste("Variant types across cancer groups in the paired longitudinal cohort", sep = " ")
rows <- 5

# Run function
fname <- paste0(PL_plots_dir, "/", "Alteration_type_timepoints_cg_id_barplots_PL.pdf")
print(fname)
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/Alteration_type_timepoints_cg_id_barplots_PL.pdf"
p <- create_stacked_barplot_variant_cg_id(df = PL_panel_df, x = x_value, palette = palette, title = title, rows = rows)
pdf(file = fname, width = 12, height = 15)
print(p)
dev.off()
quartz_off_screen 
                2 

PBTA cohort

PBTA_panel_df <- PBTA_count_df %>% 
  mutate(cg_id = str_wrap(cg_id, 12)) # Edit to fit in the plot title for the panel

# Define parameters for function
x_value <- PBTA_panel_df$tumor_descriptor
title <- paste("Variant types across cancer groups in the PBTA cohort", sep = " ")
rows <- 10

# Run function
fname <- paste0(PBTA_plots_dir, "/", "Alteration_type_timepoints_cg_id_barplots_PBTA.pdf")
print(fname)
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/Alteration_type_timepoints_cg_id_barplots_PBTA.pdf"
p <- create_stacked_barplot_variant_cg_id(df = PBTA_panel_df, x = x_value, palette = palette, title = title, rows = rows)
pdf(file = fname, width = 15, height = 28)
print(p)
dev.off()
quartz_off_screen 
                2 

Alterations per timepoint in each cancer type and molecular subtype

PL cohort

PL_panel_df <- PL_count_df %>% 
  mutate(cg_id = str_replace_all(cg_id, " ", "_"),
        # Edit to fit in the plot title for the panel
         molecular_subtype = str_wrap(molecular_subtype, 12)) 

sample <- as.character(unique(PL_panel_df$cg_id)) 
sample <- sort(sample, decreasing = FALSE)
sample
 [1] "Adamantinomatous_Craniopharyngioma"       "Atypical_Teratoid_Rhabdoid_Tumor"         "Chordoma"                                
 [4] "Choroid_plexus_carcinoma"                 "CNS_Embryonal_tumor"                      "Craniopharyngioma"                       
 [7] "Diffuse_midline_glioma"                   "Dysembryoplastic_neuroepithelial_tumor"   "Embryonal_tumor_with_multilayer_rosettes"
[10] "Ependymoma"                               "Ewing_sarcoma"                            "Ganglioglioma"                           
[13] "Glial_neuronal_tumor"                     "Hemangioblastoma"                         "High_grade_glioma"                       
[16] "Low_grade_glioma"                         "Malignant_peripheral_nerve_sheath_tumor"  "Medulloblastoma"                         
[19] "Meningioma"                               "Neuroblastoma"                            "Neurofibroma_Plexiform"                  
[22] "Pilocytic_astrocytoma"                    "Schwannoma"                              
# Loop through variable
for (i in seq_along(sample)){
  print(i)
  df_sub <- PL_panel_df %>%
    filter(cg_id == sample[i]) %>% 
    arrange(cg_id, desc(molecular_subtype), tumor_descriptor, td_plot_group_n, Variant_Classification) 

  if (i %in% c(10, 16)){
    width_value = 25
    }else{
    width_value = 10
    }
  
# Define parameters for function
x_value <- df_sub$tumor_descriptor
title <- paste(sample[i], "Variants across molecular subtypes", sep = ": ")
rows_value <- 1

# Run function
fname <- paste0(molecular_subtype_PL_plots_dir, "/", sample[i], "_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf")
print(fname)
p <- create_stacked_barplot_variant_molecular_subtype(df = df_sub, x = x_value, palette = palette, title = title, rows = rows_value)
pdf(file = fname, width = width_value, height = 6)
print(p)
dev.off()
}
[1] 1
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Adamantinomatous_Craniopharyngioma_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 2
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Atypical_Teratoid_Rhabdoid_Tumor_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 3
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Chordoma_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 4
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Choroid_plexus_carcinoma_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 5
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/CNS_Embryonal_tumor_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 6
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Craniopharyngioma_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 7
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Diffuse_midline_glioma_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 8
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Dysembryoplastic_neuroepithelial_tumor_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 9
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Embryonal_tumor_with_multilayer_rosettes_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 10
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Ependymoma_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 11
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Ewing_sarcoma_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 12
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Ganglioglioma_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 13
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Glial_neuronal_tumor_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 14
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Hemangioblastoma_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 15
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/High_grade_glioma_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 16
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Low_grade_glioma_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 17
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Malignant_peripheral_nerve_sheath_tumor_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 18
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Medulloblastoma_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 19
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Meningioma_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 20
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Neuroblastoma_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 21
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Neurofibroma_Plexiform_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 22
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Pilocytic_astrocytoma_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"
[1] 23
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/molecular_subtype_PL_plots/Schwannoma_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf"

PBTA cohort

PBTA_panel_df <- PBTA_count_df %>% 
  mutate(cg_id = str_replace_all(cg_id, " ", "_"),
         molecular_subtype = str_wrap(molecular_subtype, 12)) # Edit to fit in the plot title for the panel

sample <- as.character(unique(PBTA_panel_df$cg_id)) 
sample <- sort(sample, decreasing = FALSE)
sample
 [1] "Adamantinomatous_Craniopharyngioma"                   "Atypical_choroid_plexus_papilloma"                   
 [3] "Atypical_Teratoid_Rhabdoid_Tumor"                     "Cavernoma"                                           
 [5] "Central_neurocytoma"                                  "Chondromyxoid_fibroma"                               
 [7] "Chordoma"                                             "Choroid_plexus_carcinoma"                            
 [9] "Choroid_plexus_papilloma"                             "Choroid_plexus_tumor"                                
[11] "CNS_Burkitt's_lymphoma"                               "CNS_Embryonal_tumor"                                 
[13] "CNS_neuroblastoma"                                    "Craniopharyngioma"                                   
[15] "Desmoplastic_infantile_astrocytoma_and_ganglioglioma" "Diffuse_fibrillary_astrocytoma"                      
[17] "Diffuse_hemispheric_glioma"                           "Diffuse_intrinsic_pontine_glioma"                    
[19] "Diffuse_leptomeningeal_glioneuronal_tumor"            "Diffuse_midline_glioma"                              
[21] "Dysembryoplastic_neuroepithelial_tumor"               "Embryonal_tumor_with_multilayer_rosettes"            
[23] "Ependymoma"                                           "Epstein_Barr_virus-related_tumor"                    
[25] "Ewing_sarcoma"                                        "Extraventricular_neurocytoma"                        
[27] "Ganglioglioma"                                        "Ganglioneuroblastoma"                                
[29] "Ganglioneuroma"                                       "Germinoma"                                           
[31] "Glial_neuronal_tumor"                                 "Hemangioblastoma"                                    
[33] "High_grade_glioma"                                    "Histiocytic_tumor"                                   
[35] "Infant_type_hemispheric_glioma"                       "Inflammatory_Myofibroblastic_Tumor"                  
[37] "Langerhans_Cell_histiocytosis"                        "Low_grade_glioma"                                    
[39] "Malignant_peripheral_nerve_sheath_tumor"              "Medulloblastoma"                                     
[41] "Melanocytic_tumor"                                    "Meningioma"                                          
[43] "Mesenchymal_tumor"                                    "Metastatic_secondary_tumors"                         
[45] "Mixed_germ_cell_tumor"                                "Neuroblastoma"                                       
[47] "Neurofibroma_Plexiform"                               "Non_germinomatous_germ_cell_tumor"                   
[49] "Oligodendroglioma"                                    "Perineuroma"                                         
[51] "Pilocytic_astrocytoma"                                "Pineoblastoma"                                       
[53] "Pleomorphic_xanthoastrocytoma"                        "Rhabdomyosarcoma"                                    
[55] "Rosai_Dorfman_disease"                                "Rosette_forming_glioneuronal_tumor"                  
[57] "Sarcoma"                                              "Schwannoma"                                          
[59] "Subependymal_Giant_Cell_Astrocytoma"                  "Teratoma"                                            
# Loop through variable
for (i in seq_along(sample)){
  print(i)
  df_sub <- PBTA_panel_df %>%
    filter(cg_id == sample[i]) %>% 
    arrange(cg_id, desc(molecular_subtype), tumor_descriptor, td_plot_group_n, Variant_Classification) 

 
   if (i %in% c(23, 25, 41)){
    width_value = 25
    rows_value <- 1
    height_value = 6
   }else if (i %in% c(38)){
    width_value = 25
    rows_value <- 2
    height_value = 10
    }else{
    width_value = 10
    rows_value <- 1
    height_value = 6
    }
  
# Define parameters for function
x_value <- df_sub$tumor_descriptor
title <- paste(sample[i], "Variants across molecular subtypes", sep = ": ")


# Run function
fname <- paste0(molecular_subtype_PBTA_plots_dir, "/", sample[i], "_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf")
print(fname)
p <- create_stacked_barplot_variant_molecular_subtype(df = df_sub, x = x_value, palette = palette, title = title, rows = rows_value)
pdf(file = fname, width = width_value, height = height_value)
print(p)
dev.off()
}
[1] 1
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Adamantinomatous_Craniopharyngioma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 2
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Atypical_choroid_plexus_papilloma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 3
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Atypical_Teratoid_Rhabdoid_Tumor_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 4
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Cavernoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 5
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Central_neurocytoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 6
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Chondromyxoid_fibroma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 7
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Chordoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 8
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Choroid_plexus_carcinoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 9
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Choroid_plexus_papilloma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 10
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Choroid_plexus_tumor_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 11
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/CNS_Burkitt's_lymphoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 12
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/CNS_Embryonal_tumor_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 13
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/CNS_neuroblastoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 14
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Craniopharyngioma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 15
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Desmoplastic_infantile_astrocytoma_and_ganglioglioma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 16
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Diffuse_fibrillary_astrocytoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 17
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Diffuse_hemispheric_glioma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 18
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Diffuse_intrinsic_pontine_glioma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 19
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Diffuse_leptomeningeal_glioneuronal_tumor_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 20
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Diffuse_midline_glioma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 21
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Dysembryoplastic_neuroepithelial_tumor_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 22
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Embryonal_tumor_with_multilayer_rosettes_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 23
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Ependymoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 24
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Epstein_Barr_virus-related_tumor_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 25
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Ewing_sarcoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 26
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Extraventricular_neurocytoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 27
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Ganglioglioma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 28
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Ganglioneuroblastoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 29
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Ganglioneuroma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 30
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Germinoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 31
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Glial_neuronal_tumor_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 32
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Hemangioblastoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 33
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/High_grade_glioma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 34
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Histiocytic_tumor_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 35
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Infant_type_hemispheric_glioma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 36
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Inflammatory_Myofibroblastic_Tumor_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 37
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Langerhans_Cell_histiocytosis_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 38
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Low_grade_glioma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 39
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Malignant_peripheral_nerve_sheath_tumor_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 40
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Medulloblastoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 41
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Melanocytic_tumor_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 42
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Meningioma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 43
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Mesenchymal_tumor_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 44
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Metastatic_secondary_tumors_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 45
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Mixed_germ_cell_tumor_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 46
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Neuroblastoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 47
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Neurofibroma_Plexiform_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 48
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Non_germinomatous_germ_cell_tumor_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 49
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Oligodendroglioma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 50
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Perineuroma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 51
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Pilocytic_astrocytoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 52
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Pineoblastoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 53
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Pleomorphic_xanthoastrocytoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 54
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Rhabdomyosarcoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 55
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Rosai_Dorfman_disease_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 56
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Rosette_forming_glioneuronal_tumor_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 57
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Sarcoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 58
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Schwannoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 59
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Subependymal_Giant_Cell_Astrocytoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"
[1] 60
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PBTA/molecular_subtype_PBTA_plots/Teratoma_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf"

Alterations per timepoint in each cancer type, molecular, and kids_id

PL cohort with molecular subtype

cg_df <- PL_count_df %>%
  # Fix syntax in cancer groups names 
  mutate(cg_id = str_replace_all(cg_id, " ", "_")) 

sample <- as.character(unique(cg_df$cg_id)) 
sample <- sort(sample, decreasing = FALSE)
sample
 [1] "Adamantinomatous_Craniopharyngioma"       "Atypical_Teratoid_Rhabdoid_Tumor"         "Chordoma"                                
 [4] "Choroid_plexus_carcinoma"                 "CNS_Embryonal_tumor"                      "Craniopharyngioma"                       
 [7] "Diffuse_midline_glioma"                   "Dysembryoplastic_neuroepithelial_tumor"   "Embryonal_tumor_with_multilayer_rosettes"
[10] "Ependymoma"                               "Ewing_sarcoma"                            "Ganglioglioma"                           
[13] "Glial_neuronal_tumor"                     "Hemangioblastoma"                         "High_grade_glioma"                       
[16] "Low_grade_glioma"                         "Malignant_peripheral_nerve_sheath_tumor"  "Medulloblastoma"                         
[19] "Meningioma"                               "Neuroblastoma"                            "Neurofibroma_Plexiform"                  
[22] "Pilocytic_astrocytoma"                    "Schwannoma"                              
# Loop through variable
for (i in seq_along(sample)){
  print(i)
  df_sub <- cg_df %>%
    filter(cg_id == sample[i]) %>%
     mutate(tumor_descriptor = factor(tumor_descriptor),
         tumor_descriptor = fct_relevel(tumor_descriptor, timepoints_order_abbrev),
         Variant_Classification = factor(Variant_Classification),
         Variant_Classification = fct_relevel(Variant_Classification, variants_order)) %>% 
    arrange(tumor_descriptor, Variant_Classification)

  if (i %in% c(2, 7, 15, 18)){
    width_value = 25
    }else if (i %in% c(10, 16)){
    width_value = 36
    }else{
    width_value = 10
      }

  # Define parameters for function
  x_value <- df_sub$td_ms_plot_group
  title <- paste(sample[i], "Variants across samples", sep = ": ")
  rows_value <- 1
  
  # Run function
  fname <- paste0(kids_molecular_subtype_PL_plots_dir, "/", sample[i], "_Alteration_type_timepoints_kids_barplots_PL.pdf")
  print(fname)
  p <- create_stacked_barplot_variant_kids(df = df_sub, x = x_value, palette = palette, title = title, rows = rows_value)
  pdf(file = fname, width = width_value, height = 6)
  print(p)
  dev.off()
  }
[1] 1
Warning: There were 42 warnings in `mutate()`.
The first warning was:
ℹ In argument: `tumor_descriptor = fct_relevel(tumor_descriptor, timepoints_order_abbrev)`.
ℹ In group 1: `tumor_descriptor = Diagnosis`, `td_ms_plot_group = "Dx:ADAM"`, `cg_id = "Adamantinomatous_Craniopharyngioma"`, `molecular_subtype = "CRANIO ADAM"`,
  `Kids_First_Participant_ID = "PT_CBTW4E3X"`, `match_id = "Diagnosis_PT_CBTW4E3X"`, `Variant_Classification = Missense_Mutation`, `td_ms_plot_group_n = "Dx:ADAM
  (N=27)"`, `td_plot_group_n = "Diagnosis (N=27)"`.
Caused by warning:
! 8 unknown levels in `f`: Dx, Pro, Rec, Dec, SM, Unavail, Metastatic, and Residual
ℹ Run ]8;;ide:run:dplyr::last_dplyr_warnings()dplyr::last_dplyr_warnings()]8;; to see the 41 remaining warnings.
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Adamantinomatous_Craniopharyngioma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 2
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Atypical_Teratoid_Rhabdoid_Tumor_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 3
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Chordoma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 4
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Choroid_plexus_carcinoma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 5
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/CNS_Embryonal_tumor_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 6
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Craniopharyngioma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 7
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Diffuse_midline_glioma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 8
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Dysembryoplastic_neuroepithelial_tumor_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 9
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Embryonal_tumor_with_multilayer_rosettes_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 10
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Ependymoma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 11
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Ewing_sarcoma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 12
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Ganglioglioma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 13
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Glial_neuronal_tumor_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 14
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Hemangioblastoma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 15
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/High_grade_glioma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 16
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Low_grade_glioma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 17
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Malignant_peripheral_nerve_sheath_tumor_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 18
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Medulloblastoma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 19
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Meningioma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 20
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Neuroblastoma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 21
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Neurofibroma_Plexiform_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 22
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Pilocytic_astrocytoma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 23
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_molecular_subtype_PL_plots/Schwannoma_Alteration_type_timepoints_kids_barplots_PL.pdf"

PL cohort without molecular subtype

cg_df <- PL_count_df %>%
  # Fix syntax in cancer groups names 
  mutate(cg_id = str_replace_all(cg_id, " ", "_"))

sample <- as.character(unique(cg_df$cg_id)) 
sample <- sort(sample, decreasing = FALSE)
sample
 [1] "Adamantinomatous_Craniopharyngioma"       "Atypical_Teratoid_Rhabdoid_Tumor"         "Chordoma"                                
 [4] "Choroid_plexus_carcinoma"                 "CNS_Embryonal_tumor"                      "Craniopharyngioma"                       
 [7] "Diffuse_midline_glioma"                   "Dysembryoplastic_neuroepithelial_tumor"   "Embryonal_tumor_with_multilayer_rosettes"
[10] "Ependymoma"                               "Ewing_sarcoma"                            "Ganglioglioma"                           
[13] "Glial_neuronal_tumor"                     "Hemangioblastoma"                         "High_grade_glioma"                       
[16] "Low_grade_glioma"                         "Malignant_peripheral_nerve_sheath_tumor"  "Medulloblastoma"                         
[19] "Meningioma"                               "Neuroblastoma"                            "Neurofibroma_Plexiform"                  
[22] "Pilocytic_astrocytoma"                    "Schwannoma"                              
# Loop through variable
for (i in seq_along(sample)){
  print(i)
  df_sub <- cg_df %>%
    filter(cg_id == sample[i]) 

  if (i %in% c(2, 7, 15, 18)){
    width_value = 25
    }else if (i %in% c(10, 16)){
    width_value = 28
    }else{
    width_value = 10
      }

  # Define parameters for function
  x_value <- df_sub$td_ms_plot_group_n
  title <- paste(sample[i], "Variants across samples", sep = ": ")
  rows <- 1
  
  # Run function
  fname <- paste0(kids_PL_plots_dir, "/", sample[i], "_Alteration_type_timepoints_kids_barplots_PL.pdf")
  print(fname)
  p <- create_stacked_barplot_variant_kids(df = df_sub, x = x_value, palette = palette, title = title, rows = rows)
  pdf(file = fname, width = width_value, height = 6)
  print(p)
  dev.off()
  }
[1] 1
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Adamantinomatous_Craniopharyngioma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 2
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Atypical_Teratoid_Rhabdoid_Tumor_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 3
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Chordoma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 4
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Choroid_plexus_carcinoma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 5
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/CNS_Embryonal_tumor_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 6
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Craniopharyngioma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 7
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Diffuse_midline_glioma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 8
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Dysembryoplastic_neuroepithelial_tumor_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 9
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Embryonal_tumor_with_multilayer_rosettes_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 10
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Ependymoma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 11
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Ewing_sarcoma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 12
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Ganglioglioma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 13
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Glial_neuronal_tumor_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 14
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Hemangioblastoma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 15
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/High_grade_glioma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 16
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Low_grade_glioma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 17
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Malignant_peripheral_nerve_sheath_tumor_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 18
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Medulloblastoma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 19
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Meningioma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 20
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Neuroblastoma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 21
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Neurofibroma_Plexiform_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 22
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Pilocytic_astrocytoma_Alteration_type_timepoints_kids_barplots_PL.pdf"
[1] 23
[1] "/Users/chronia/CHOP/GitHub/pbta-tumor-evolution/analyses/tmb-vaf-longitudinal/plots/Alteration_type_barplots_PL/kids_PL_plots/Schwannoma_Alteration_type_timepoints_kids_barplots_PL.pdf"

---
title: "Classification of Variants in the paired longitudinal (PL) and PBTA cohorts"
author: 'Antonia Chroni <chronia@chop.edu> for D3B'
date: "2023"
output:
  html_notebook:
    toc: TRUE
    toc_float: TRUE
---

# Set up
```{r load-library}
suppressPackageStartupMessages({
  library(tidyverse)
})
```

# Directories and File Inputs/Outputs
```{r set-dir-and-file-names}
# Detect the ".git" folder -- this will be in the project root directory
# Use this as the root directory to ensure proper sourcing of functions 
# no matter where this is called from
root_dir <- rprojroot::find_root(rprojroot::has_dir(".git"))
analysis_dir <- file.path(root_dir, "analyses", "tmb-vaf-longitudinal")
results_dir <- file.path(analysis_dir, "results")
input_dir <- file.path(analysis_dir, "input")
files_dir <- file.path(root_dir, "analyses", "sample-distribution-analysis", "results")

# Input files for the paired longitudinal (PL) cohort
pbta_file <- file.path(files_dir, "pbta.tsv") # file from add-sample-distribution module
genomic_paired_file <- file.path(files_dir, "genomic_assays_matched_time_points.tsv")
tmb_vaf_file <- file.path(results_dir, "tmb_vaf_genomic.tsv")
palette_file <- file.path(root_dir, "figures", "palettes", "oncoprint_color_palette.tsv")


# Input files for the PBTA cohort
maf_file <- file.path(results_dir, "maf.tsv")
tmb_file <- file.path(input_dir, "snv-mutation-tmb-coding.tsv")


# File path to PL plot directory
PL_plots_dir <-
  file.path(analysis_dir, "plots", "Alteration_type_barplots_PL")
if (!dir.exists(PL_plots_dir)) {
  dir.create(PL_plots_dir)
}

# File path to kids_PL_plots directory
kids_PL_plots_dir <-
  file.path(PL_plots_dir, "kids_PL_plots")
if (!dir.exists(kids_PL_plots_dir)) {
  dir.create(kids_PL_plots_dir)
}

# File path to kids_molecular_subtype_PL_plots_dir directory
kids_molecular_subtype_PL_plots_dir <-
  file.path(PL_plots_dir, "kids_molecular_subtype_PL_plots")
if (!dir.exists(kids_molecular_subtype_PL_plots_dir)) {
  dir.create(kids_molecular_subtype_PL_plots_dir)
}


# File path to molecular_subtype_PL_plots directory
molecular_subtype_PL_plots_dir <-
  file.path(PL_plots_dir, "molecular_subtype_PL_plots")
if (!dir.exists(molecular_subtype_PL_plots_dir)) {
  dir.create(molecular_subtype_PL_plots_dir)
}

# File path to PBTA plot directory
PBTA_plots_dir <-
  file.path(analysis_dir, "plots", "Alteration_type_barplots_PBTA")
if (!dir.exists(PBTA_plots_dir)) {
  dir.create(PBTA_plots_dir)
}


# File path to molecular_subtype_PBTA_plots directory
molecular_subtype_PBTA_plots_dir <-
  file.path(PBTA_plots_dir, "molecular_subtype_PBTA_plots")
if (!dir.exists(molecular_subtype_PBTA_plots_dir)) {
  dir.create(molecular_subtype_PBTA_plots_dir)
}

source(paste0(root_dir, "/figures/scripts/theme.R"))
source(paste0(analysis_dir, "/util/function-create-barplot.R"))
```

# Read in data and process

```{r }
# Vector to order timepoints
timepoints_order <- c("Diagnosis", "Progressive", "Recurrence", "Deceased", "Second Malignancy", "Unavailable", "Metastatic", "Residual")
timepoints_order_abbrev <- c("Dx", "Pro", "Rec", "Dec", "SM", "Unavail", "Metastatic", "Residual")

# Vector to order Variant_Classification
variants_order <- c("Frame_Shift_Del", "Frame_Shift_Ins", "In_Frame_Del", 
                    "In_Frame_Ins", "Missense_Mutation", "Nonsense_Mutation", 
                    "Nonstop_Mutation", "Splice_Site", "Translation_Start_Site")
```
## PL cohort

```{r load-process-inputs-PL}
pbta_df <- readr::read_tsv(pbta_file, guess_max = 100000, show_col_types = FALSE) %>% 
  select(Kids_First_Participant_ID, Kids_First_Biospecimen_ID, cg_multiple, cg_id, cgGFAC, tumor_descriptor, molecular_subtype) %>%  #plot_group
  mutate(tumor_descriptor_abbrev = case_when(grepl("Diagnosis", tumor_descriptor) ~ "Dx",
                               grepl("Progressive", tumor_descriptor) ~ "Pro",
                               grepl("Recurrence", tumor_descriptor) ~ "Rec",
                               grepl("Deceased", tumor_descriptor) ~ "Dec",
                               grepl("Second Malignancy", tumor_descriptor) ~ "SM",
                               grepl("Unavailable", tumor_descriptor) ~ "Unavail",
                              TRUE ~ tumor_descriptor),
         molecular_subtype = str_replace(molecular_subtype, ",", ""),
         molecular_subtype_edited = str_replace(molecular_subtype, "^\\S* ", ""),
         
         # create unique identifier for timepoint and molecular subtype
         td_ms_plot_group = paste(tumor_descriptor_abbrev, molecular_subtype_edited, sep = ":")) 
  

# This includes non synonymous mutations as described in the `01-preporcess-data.Rmd`
tmb_vaf_df <- readr::read_tsv(tmb_vaf_file, guess_max = 100000, show_col_types = FALSE) %>% 
  filter(!tmb >= 10) %>% 
  select(Kids_First_Biospecimen_ID, Variant_Classification, gene_protein, mutation_count,	region_size, tmb, VAF) %>% 
  filter(!is.na(Variant_Classification))

# List with patients with paired longitudinal genomic specimens
genomic_paired_df <- readr::read_tsv(genomic_paired_file, guess_max = 100000, show_col_types = FALSE) %>%
  left_join(pbta_df, by = c("Kids_First_Participant_ID")) %>% 
  left_join(tmb_vaf_df, by = c("Kids_First_Biospecimen_ID")) %>%
  filter(!is.na(tmb))

# Number of patients with TMB information
no_samples_with_tmb <- print(length(unique(genomic_paired_df$Kids_First_Participant_ID)))

# Attention as some bs specimen might not have TMB.
# If that happens, we will end up with samples lacking timepoints.
# Let's identify these samples and remove them.
PL_df <- genomic_paired_df %>%
  select(Kids_First_Participant_ID, tumor_descriptor) %>% 
  unique() %>%
  arrange(Kids_First_Participant_ID, tumor_descriptor) %>%
  group_by(Kids_First_Participant_ID) %>%
  summarize(tumor_descriptor_sum = str_c(tumor_descriptor, collapse = ";")) %>%
  filter(!tumor_descriptor_sum %in% c("Diagnosis", "Progressive", "Recurrence", "Second Malignancy", "Unavailable", "Deceased", "Progressive;Progressive")) %>%
  left_join(genomic_paired_df, by = c("Kids_First_Participant_ID")) %>%
  filter(!cg_id == "NA",
         !tumor_descriptor == "Not Reported") %>% 
  mutate(match_id = paste(tumor_descriptor, Kids_First_Participant_ID, sep = "_"),
         cg_id = str_replace(cg_id, c("/|-"), " "))
  
# Let's summarize td_ms_plot_group and use this for visualization purposes
PL_td_ms_plot_group_n_df <- PL_df %>% 
  dplyr::count(cg_id, td_ms_plot_group) %>% 
  dplyr::mutate(td_ms_plot_group_n = glue::glue("{td_ms_plot_group} (N={n})")) %>% 
  dplyr::rename(td_ms_plot_group_number = n) 


# Let's summarize tumor_descriptor and use this for visualization purposes
PL_td_plot_group_n_df <- PL_df %>% 
  dplyr::count(cg_id, tumor_descriptor) %>% 
  dplyr::mutate(td_plot_group_n = glue::glue("{tumor_descriptor} (N={n})")) %>% 
  dplyr::rename(td_plot_group_number = n)

# Let's count number of samples 
PL_count_df <- PL_df %>%
  left_join(PL_td_ms_plot_group_n_df) %>%
  left_join(PL_td_plot_group_n_df) %>%
  filter(!is.na(Variant_Classification)) %>% 
  # remove if total #samples per timepoint is less than 2
  #filter(!td_ms_plot_group_number <= 2) %>% 
  group_by(tumor_descriptor, td_ms_plot_group, cg_id, molecular_subtype, Kids_First_Participant_ID, match_id, Variant_Classification, td_ms_plot_group_n, td_plot_group_n) %>% 
  dplyr::count(Kids_First_Participant_ID) %>% 
  mutate(tumor_descriptor = factor(tumor_descriptor),
         tumor_descriptor = fct_relevel(tumor_descriptor, timepoints_order),
         Variant_Classification = factor(Variant_Classification),
         Variant_Classification = fct_relevel(Variant_Classification, variants_order)) %>% 
  arrange(cg_id, tumor_descriptor, td_plot_group_n, Variant_Classification, desc(molecular_subtype)) 

# Number of patients with TMB information and paired timepoints
no_samples <- print(length(unique(PL_count_df$Kids_First_Participant_ID)))

``` 

## PBTA cohort

```{r load-process-inputs-PBTA}
tmb_df <- readr::read_tsv(tmb_file, guess_max = 100000, show_col_types = FALSE) %>% 
  dplyr::rename(Kids_First_Biospecimen_ID = Tumor_Sample_Barcode) # change name of the biospecimen to match the one from the histologies files

tmb_vaf_df <- readr::read_tsv(maf_file, guess_max = 100000, show_col_types = FALSE) %>%
  left_join(tmb_df, by = c("Kids_First_Biospecimen_ID")) %>% 
  filter(!tmb >= 10,
         !is.na(tmb)) 

PBTA_df <- pbta_df %>% 
  left_join(tmb_vaf_df, by = c("Kids_First_Biospecimen_ID")) %>% 
  filter(!cg_id == "NA",
         !tumor_descriptor == "Not Reported",
         !is.na(Variant_Classification)) %>% 
  mutate(match_id = paste(tumor_descriptor, Kids_First_Participant_ID, sep = "_"),
         cg_id = str_replace(cg_id, c("/|-"), " "))

# Number of patients with TMB information
no_samples <- print(length(unique(PBTA_df$Kids_First_Participant_ID)))


# Let's summarize tumor_descriptor and use this for visualization purposes
PBTA_td_plot_group_n_df <- PBTA_df %>% 
  dplyr::count(cg_id, tumor_descriptor) %>% 
  dplyr::mutate(td_plot_group_n = glue::glue("{tumor_descriptor} (N={n})")) %>% 
  dplyr::rename(td_plot_group_number = n)

# Let's count number of samples 
PBTA_count_df <- PBTA_df %>% 
  left_join(PBTA_td_plot_group_n_df, by = join_by("cg_id", "tumor_descriptor")) %>% 
  filter(!is.na(Variant_Classification)) %>% 
  group_by(tumor_descriptor, cg_id, molecular_subtype, Kids_First_Participant_ID, match_id, Variant_Classification, td_plot_group_n) %>% 
  dplyr::count(Kids_First_Participant_ID) %>% 
  mutate(tumor_descriptor = factor(tumor_descriptor),
         tumor_descriptor = fct_relevel(tumor_descriptor, timepoints_order),
         Variant_Classification = factor(Variant_Classification),
         Variant_Classification = fct_relevel(Variant_Classification, variants_order)) %>% 
  arrange(cg_id, tumor_descriptor, td_plot_group_n, Variant_Classification, desc(molecular_subtype)) 

```



# Define parameters for plots

```{r define-parameters-for-plots}
# Read color palette
palette_df <- readr::read_tsv(palette_file, guess_max = 100000, show_col_types = FALSE) %>% 
  mutate(hex_codes = case_when(grepl("#000000", hex_codes) ~ "orange",
                               TRUE ~ hex_codes),
    color_names = factor(color_names),
         color_names = fct_relevel(color_names, variants_order)) %>% 
  arrange(color_names)

         
# Define and order palette
palette <- palette_df$hex_codes
names(palette) <- palette_df$color_names
```

# Alterations per timepoint

## PL cohort

```{r plot-timepoint-PL, fig.width = 6, fig.height = 6, fig.fullwidth = TRUE}
# Define parameters for function
x_value <- PL_count_df$tumor_descriptor
title <- paste("Variant types in the paired longitudinal cohort", sep = " ")

# Run function
fname <- paste0(PL_plots_dir, "/", "Alteration_type_timepoints_barplots_PL.pdf")
print(fname)
p <- create_stacked_barplot_variant(df = PL_count_df, x = x_value, palette = palette, title = title)
pdf(file = fname, width = 6, height = 6)
print(p)
dev.off()
```

## PBTA cohort

```{r plot-timepoint-PBTA, fig.width = 6, fig.height = 6, fig.fullwidth = TRUE}
# Define parameters for function
x_value <- PBTA_count_df$tumor_descriptor
title <- paste("Variant types in the PBTA cohort", sep = " ")

# Run function
fname <- paste0(PBTA_plots_dir, "/", "Alteration_type_timepoints_barplots_PBTA.pdf")
print(fname)
p <- create_stacked_barplot_variant(df = PBTA_count_df, x = x_value, palette = palette, title = title)
pdf(file = fname, width = 6, height = 6)
print(p)
dev.off()
```


# Alterations per timepoint in each cancer type

## PL cohort

```{r plot-cg-id-PL, fig.width = 12, fig.height = 15, fig.fullwidth = TRUE}
PL_panel_df <- PL_count_df %>% 
  mutate(cg_id = str_wrap(cg_id, 12)) # Edit to fit in the plot title for the panel

# Define parameters for function
x_value <- PL_panel_df$tumor_descriptor
title <- paste("Variant types across cancer groups in the paired longitudinal cohort", sep = " ")
rows <- 5

# Run function
fname <- paste0(PL_plots_dir, "/", "Alteration_type_timepoints_cg_id_barplots_PL.pdf")
print(fname)
p <- create_stacked_barplot_variant_cg_id(df = PL_panel_df, x = x_value, palette = palette, title = title, rows = rows)
pdf(file = fname, width = 12, height = 15)
print(p)
dev.off()
```

## PBTA cohort


```{r plot-cg-id-PBTA, fig.width = 15, fig.height = 28, fig.fullwidth = TRUE}
PBTA_panel_df <- PBTA_count_df %>% 
  mutate(cg_id = str_wrap(cg_id, 12)) # Edit to fit in the plot title for the panel

# Define parameters for function
x_value <- PBTA_panel_df$tumor_descriptor
title <- paste("Variant types across cancer groups in the PBTA cohort", sep = " ")
rows <- 10

# Run function
fname <- paste0(PBTA_plots_dir, "/", "Alteration_type_timepoints_cg_id_barplots_PBTA.pdf")
print(fname)
p <- create_stacked_barplot_variant_cg_id(df = PBTA_panel_df, x = x_value, palette = palette, title = title, rows = rows)
pdf(file = fname, width = 15, height = 28)
print(p)
dev.off()
```


# Alterations per timepoint in each cancer type and molecular subtype

## PL cohort

```{r plot-molecular-subtype-PL, fig.width = 12, fig.height = 6, fig.fullwidth = TRUE}
PL_panel_df <- PL_count_df %>% 
  mutate(cg_id = str_replace_all(cg_id, " ", "_"),
        # Edit to fit in the plot title for the panel
         molecular_subtype = str_wrap(molecular_subtype, 12)) 

sample <- as.character(unique(PL_panel_df$cg_id)) 
sample <- sort(sample, decreasing = FALSE)
sample


# Loop through variable
for (i in seq_along(sample)){
  print(i)
  df_sub <- PL_panel_df %>%
    filter(cg_id == sample[i]) %>% 
    arrange(cg_id, desc(molecular_subtype), tumor_descriptor, td_plot_group_n, Variant_Classification) 

  if (i %in% c(10, 16)){
    width_value = 25
    }else{
    width_value = 10
    }
  
# Define parameters for function
x_value <- df_sub$tumor_descriptor
title <- paste(sample[i], "Variants across molecular subtypes", sep = ": ")
rows_value <- 1

# Run function
fname <- paste0(molecular_subtype_PL_plots_dir, "/", sample[i], "_Alteration_type_timepoints_molecular_subtype_barplots_PL.pdf")
print(fname)
p <- create_stacked_barplot_variant_molecular_subtype(df = df_sub, x = x_value, palette = palette, title = title, rows = rows_value)
pdf(file = fname, width = width_value, height = 6)
print(p)
dev.off()
}

```

## PBTA cohort


```{r plot-molecular-subtype-PBTA, fig.width = 12, fig.height = 6, fig.fullwidth = TRUE}
PBTA_panel_df <- PBTA_count_df %>% 
  mutate(cg_id = str_replace_all(cg_id, " ", "_"),
         molecular_subtype = str_wrap(molecular_subtype, 12)) # Edit to fit in the plot title for the panel

sample <- as.character(unique(PBTA_panel_df$cg_id)) 
sample <- sort(sample, decreasing = FALSE)
sample


# Loop through variable
for (i in seq_along(sample)){
  print(i)
  df_sub <- PBTA_panel_df %>%
    filter(cg_id == sample[i]) %>% 
    arrange(cg_id, desc(molecular_subtype), tumor_descriptor, td_plot_group_n, Variant_Classification) 

 
   if (i %in% c(23, 25, 41)){
    width_value = 25
    rows_value <- 1
    height_value = 6
   }else if (i %in% c(38)){
    width_value = 25
    rows_value <- 2
    height_value = 10
    }else{
    width_value = 10
    rows_value <- 1
    height_value = 6
    }
  
# Define parameters for function
x_value <- df_sub$tumor_descriptor
title <- paste(sample[i], "Variants across molecular subtypes", sep = ": ")


# Run function
fname <- paste0(molecular_subtype_PBTA_plots_dir, "/", sample[i], "_Alteration_type_timepoints_molecular_subtype_barplots_PBTA.pdf")
print(fname)
p <- create_stacked_barplot_variant_molecular_subtype(df = df_sub, x = x_value, palette = palette, title = title, rows = rows_value)
pdf(file = fname, width = width_value, height = height_value)
print(p)
dev.off()
}

```


# Alterations per timepoint in each cancer type, molecular, and kids_id

## PL cohort with molecular subtype

```{r plot-cg-id-molecular-subtype-kids-PL, fig.width = 10, fig.height = 6, fig.fullwidth = TRUE}
cg_df <- PL_count_df %>%
  # Fix syntax in cancer groups names 
  mutate(cg_id = str_replace_all(cg_id, " ", "_")) 

sample <- as.character(unique(cg_df$cg_id)) 
sample <- sort(sample, decreasing = FALSE)
sample


# Loop through variable
for (i in seq_along(sample)){
  print(i)
  df_sub <- cg_df %>%
    filter(cg_id == sample[i]) %>%
     mutate(tumor_descriptor = factor(tumor_descriptor),
         tumor_descriptor = fct_relevel(tumor_descriptor, timepoints_order_abbrev),
         Variant_Classification = factor(Variant_Classification),
         Variant_Classification = fct_relevel(Variant_Classification, variants_order)) %>% 
    arrange(tumor_descriptor, Variant_Classification)

  if (i %in% c(2, 7, 15, 18)){
    width_value = 25
    }else if (i %in% c(10, 16)){
    width_value = 36
    }else{
    width_value = 10
      }

  # Define parameters for function
  x_value <- df_sub$td_ms_plot_group
  title <- paste(sample[i], "Variants across samples", sep = ": ")
  rows_value <- 1
  
  # Run function
  fname <- paste0(kids_molecular_subtype_PL_plots_dir, "/", sample[i], "_Alteration_type_timepoints_kids_barplots_PL.pdf")
  print(fname)
  p <- create_stacked_barplot_variant_kids(df = df_sub, x = x_value, palette = palette, title = title, rows = rows_value)
  pdf(file = fname, width = width_value, height = 6)
  print(p)
  dev.off()
  }

```

## PL cohort without molecular subtype

```{r plot-cg-id-kids-PL, fig.width = 10, fig.height = 6, fig.fullwidth = TRUE}
cg_df <- PL_count_df %>%
  # Fix syntax in cancer groups names 
  mutate(cg_id = str_replace_all(cg_id, " ", "_"))

sample <- as.character(unique(cg_df$cg_id)) 
sample <- sort(sample, decreasing = FALSE)
sample


# Loop through variable
for (i in seq_along(sample)){
  print(i)
  df_sub <- cg_df %>%
    filter(cg_id == sample[i]) 

  if (i %in% c(2, 7, 15, 18)){
    width_value = 25
    }else if (i %in% c(10, 16)){
    width_value = 28
    }else{
    width_value = 10
      }

  # Define parameters for function
  x_value <- df_sub$td_ms_plot_group_n
  title <- paste(sample[i], "Variants across samples", sep = ": ")
  rows <- 1
  
  # Run function
  fname <- paste0(kids_PL_plots_dir, "/", sample[i], "_Alteration_type_timepoints_kids_barplots_PL.pdf")
  print(fname)
  p <- create_stacked_barplot_variant_kids(df = df_sub, x = x_value, palette = palette, title = title, rows = rows)
  pdf(file = fname, width = width_value, height = 6)
  print(p)
  dev.off()
  }

```

```{r echo=TRUE}
sessionInfo()
```
